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Senior Data Scientist
Machine learning and data science are at the heart of Jabama's mission to make travel smarter, more personal, and more efficient We're building systems that understand user intent, forecast demand, optimize prices, and connect travelers to the right experiences at the right time As a Data Scientist at Jabama, you will design, build, and maintain models and data-driven systems that power these decisions You'll combine rigorous statistical thinking with strong software engineering skills to deliver reliable, explainable, and high-impact solutions at scale	Job Description
Design and implement scalable data science solutions across the full ML lifecycle, from problem framing and data modeling to production deployment and monitoring Develop and maintain predictive and inferential models for a wide range of challenges, including forecasting, anomaly detection, regression, and classification Apply solid statistical reasoning and experimental design to ensure model interpretability, robustness, and trustworthiness Build, maintain, and optimize data and ML pipelines using tools like Spark, Airflow, and modern ML frameworks Develop and maintain monitoring dashboards and visibility tools to track model health, data drift, and business impact Collaborate closely with data engineers, analysts, and product managers to translate business objectives into measurable, data-driven outcomes Write clean, production-ready code and reusable components that adhere to engineering best practices Continuously improve data quality, model explainability, and overall system reliability Stay current with the latest research and technologies in machine learning, data engineering, and large-scale system design	What You'll Be Doing
Master's degree in Computer Science, Artificial intelligence, or another related quantitative field years 3+ of professional experience applying data science and machine learning in production environments Strong understanding of statistics, probability theory, and mathematical modeling Deep knowledge of machine learning fundamentals and practical experience across multiple paradigms, including neural networks, decision trees, reinforcement learning, and statistical modeling Proven experience with real-world ML applications such as regression, classification, anomaly detection, and forecasting Excellent proficiency in Python and SQL, with strong software engineering and problem-solving skills Experience building scalable pipelines and production systems using Spark, Airflow, or similar tools Familiarity with transactional and analytical databases such as PostgreSQL and ClickHouse Experience of developing monitoring and visualization dashboards that translate technical performance into actionable insights Strong collaboration and communication skills Able to work effectively with stakeholders across disciplines and drive alignment between technical and business goals Proactive mindset, sense of ownership, and a passion for technical excellence	Requirements
Results-driven, creative, and solution-oriented Highly organized with strong attention to detail Adaptable to fast-paced and dynamic environments Team player with a strong sense of ownership and accountability	Personal Attributes